Various efficient techniques have been proposed for the
related range max problem [1]}, [2]}, but
they do not necessarily generalize.
Instead, for the range top-\(k\)  problem, we can partition sparse data cubes into customized data structures to speed up
queries by an order of
magnitude [3]}, [4]}, [5]}. We can also answer range top-\(k\)  queries using
RD-trees [6]} or R-trees [7]}.
In tag clouds, precision is not required and accuracy is less important; only the most significant tags
are typically needed. Further, if all tags have similar weights, then any
subset of tag may form an acceptable tag cloud.
